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MODEL1006230054 - Lockwood2006_PKPD_AlzheimersDisease

 

The following model is part of the non-curated branch of BioModels Database. While the syntax of the model has been verified, its semantics remains unchecked. Any annotation present in the models is not a product of BioModels' annotators. We are doing our best to incorporate this model into the curated branch as soon as possible. In the meantime, we display only limited metadata here. For further information about the model, please download the SBML file.


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Reference Publication
Publication ID: 16906456
Lockwood P, Ewy W, Hermann D, Holford N.
Application of clinical trial simulation to compare proof-of-concept study designs for drugs with a slow onset of effect; an example in Alzheimer's disease.
Pharm. Res. 2006 Sep; 23(9): 2050-2059
Pfizer Global Research and Development, Ann Arbor, Michigan, USA. peter.lockwood@pfizer.com  [more]
Model
Original Model: CellML logo
Submitter: Camille Laibe
Submission Date: 23 Jun 2010 10:12:15 UTC
Last Modification Date: 25 Jun 2010 14:17:54 UTC
Creation Date: 25 Jun 2010 14:17:54 UTC
Encoders:  James Lawson
bqmodel:isDerivedFrom PubMed 1454836
PubMed 1454835
bqbiol:isVersionOf Gene Ontology response to drug
Human Disease Ontology Alzheimer's disease
Notes

This a model from the article:
Application of clinical trial simulation to compare proof-of-concept study designs for drugs with a slow onset of effect; an example in Alzheimer's disease.
Lockwood P, Ewy W, Hermann D, Holford N. Pharm Res 2006 Sep;23(9):2050-9 16906456 ,
Abstract:
OBJECTIVE: Clinical trial simulation (CTS) was used to select a robust design to test the hypothesis that a new treatment was effective for Alzheimer's disease (AD). Typically, a parallel group, placebo controlled, 12-week trial in 200-400 AD patients would be used to establish drug effect relative to placebo (i.e., Ho: Drug Effect = 0). We evaluated if a crossover design would allow smaller and shorter duration trials. MATERIALS AND METHODS: A family of plausible drug and disease models describing the time course of the AD assessment scale (ADAS-Cog) was developed based on Phase I data and literature reports of other treatments for AD. The models included pharmacokinetic, pharmacodynamic, disease progression, and placebo components. Eight alternative trial designs were explored via simulation. One hundred replicates of each combination of drug and disease model and trial design were simulated. A 'positive trial' reflecting drug activity was declared considering both a dose trend test (p < 0.05) and pair-wise comparisons to placebo (p < 0.025). RESULTS: A 4 x 4 Latin Square design was predicted to have at least 80% power to detect activity across a range of drug and disease models. The trial design was subsequently implemented and the trial was completed. Based on the results of the actual trial, a conclusive decision about further development was taken. The crossover design provided enhanced power over a parallel group design due to the lower residual variability. CONCLUSION: CTS aided the decision to use a more efficient proof of concept trial design, leading to savings of up to US 4 M dollars in direct costs and a firm decision 8-12 months earlier than a 12-week parallel group trial.

This model was taken from the CellML repository and automatically converted to SBML.
The original model was: Lockwood P, Ewy W, Hermann D, Holford N. (2006) - version=1.0
The original CellML model was created by:
James Lawson
j.lawson@auckland.ac.nz
The University of Auckland

This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..

To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

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